Work

Subject-specific whole-lung CFPD coupled with PBPK/PD to predict inhaled bronchodilator response in asthmatic and healthy subjects

Year: 2026

Type: article

Abstract: Accurate prediction of bronchodilator performance remains challenging. We present a coupled computational fluid and particle dynamics (CFPD) and physiologically-based pharmacokinetic /pharmacodynamics (PBPK/PD) framework that leverages subject-specific CT-derived airway trees and airflow distributions to model regional lung exposure and the resulting clinical effect, quantified as the change in Forced Expiratory Volume in 1 second (∆FEV1). Data from six asthmatic and ten healthy subjects were analyzed. CFPD simulations predicted subject-specific airflow and drug deposition by airway generation for inhalation of 400 μg albuterol using a metered dose inhaler (MDI) and a dry powder inhaler (DPI). The deposited dose was input into the PBPK model at the epithelial lining fluid (ELF) to predict drug concentrations in plasma and tissues. The PD model predicted ∆FEV1 at the subepithelium effect-site. Two key observations emerged. First, MDI use shifted the inhaled dose toward the respiratory region, whereas DPI delivery resulted in greater deposition in generations G2-G5. Second, asthmatic subjects exhibited higher resistance than healthy subjects in generations G5-G10, increasing the bronchodilatory effect and explaining the larger early ∆FEV1. Fitted PD model parameters, yielded a half-maximal effective concentration (EC50 =1.1±0.07 nM) and Hill slope (n =1.6±0.1), with R2 = 0.98. In summary, we developed a subject-specific coupled CFPD-PBPK/PD framework that integrates CT-derived airway structure, lung ventilation, and inhalation profiles to predict inhaled albuterol exposure in plasma and ELF, as well as the resulting ∆FEV1 clinical response. This approach has the potential to inform inhaler selection, optimize dosing strategies, and enable disease-specific inhalational therapies.

Source: Journal of Aerosol Science

DOI: 10.1016/j.jaerosci.2026.106784

Authors: Prathish K. Rajaraman, Xuan Zhang, Alejandro P. Comellas, Eric A. Hoffman, Ching-Long Lin

Institution: University of Iowa

Language: English

Topic: Inhalation and Respiratory Drug Delivery

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,850